---
base_model: ai-forever/ruT5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: skilltext
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# skilltext

This model is a fine-tuned version of [ai-forever/ruT5-base](https://huggingface.co/ai-forever/ruT5-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0577
- Rouge1: 30.9205
- Rouge2: 11.9258
- Rougel: 26.6497
- Rougelsum: 26.4407
- Gen Len: 18.6875

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-------:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| No log        | 1.6129  | 50   | 1.8405          | 16.798  | 2.7473  | 15.7599 | 15.6863   | 19.0    |
| No log        | 3.2258  | 100  | 1.4606          | 19.3942 | 7.4911  | 18.9911 | 18.8407   | 18.875  |
| No log        | 4.8387  | 150  | 1.3583          | 27.0146 | 13.8805 | 24.3188 | 24.2122   | 18.6875 |
| No log        | 6.4516  | 200  | 1.2490          | 32.855  | 15.9819 | 31.0776 | 30.8624   | 18.75   |
| No log        | 8.0645  | 250  | 1.1590          | 30.3762 | 11.8253 | 27.5559 | 27.2332   | 18.5625 |
| No log        | 9.6774  | 300  | 1.1469          | 37.2275 | 17.107  | 33.4177 | 33.3688   | 18.4375 |
| No log        | 11.2903 | 350  | 1.1364          | 34.3596 | 15.6845 | 30.8838 | 31.0842   | 18.625  |
| No log        | 12.9032 | 400  | 1.0927          | 34.9322 | 15.8027 | 30.2917 | 30.1379   | 18.6875 |
| No log        | 14.5161 | 450  | 1.0672          | 32.2753 | 15.7727 | 28.1883 | 27.8978   | 18.6875 |
| 1.8948        | 16.1290 | 500  | 1.0721          | 37.6573 | 15.6507 | 32.7817 | 32.742    | 18.5625 |
| 1.8948        | 17.7419 | 550  | 1.0692          | 34.958  | 15.3422 | 30.4656 | 30.3306   | 18.5    |
| 1.8948        | 19.3548 | 600  | 1.0577          | 30.9205 | 11.9258 | 26.6497 | 26.4407   | 18.6875 |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.2.2
- Datasets 2.12.0
- Tokenizers 0.19.1